This research article presents an energy- efficient smart home heating system that uses a renew-able energy source and incorporates fuzzy control design. The objective of the study is to design a heating system that optimizes energy consumption while providing a comfortable indoor temperature. The main methods used in the study include the integration of a renewable energy source, such as solar energy or geothermal energy, with a fuzzy control system that adjusts the heating power based on indoor and outdoor temperature, humidity, and occupancy. The main results of the study show that the proposed heating system can reduce energy consumption by up to 40% compared to conventional heating systems, while maintaining a comfortable indoor temperature. The fuzzy control system provides precise control of the heating power and ensures efficient use of the renewable energy source. The main conclusion of the article is that the proposed smart home heating system is a viable solution for reducing energy consumption and promoting a sustainable lifestyle, especially in areas with abundant renewable energy sources.
{"title":"Energy efficient smart home heating system using renewable energy source with fuzzy control design","authors":"János Simon, Róbert x Róbert Sánta","doi":"10.31181/dmame622023825","DOIUrl":"https://doi.org/10.31181/dmame622023825","url":null,"abstract":"This research article presents an energy- efficient smart home heating system that uses a renew-able energy source and incorporates fuzzy control design. The objective of the study is to design a heating system that optimizes energy consumption while providing a comfortable indoor temperature. The main methods used in the study include the integration of a renewable energy source, such as solar energy or geothermal energy, with a fuzzy control system that adjusts the heating power based on indoor and outdoor temperature, humidity, and occupancy. The main results of the study show that the proposed heating system can reduce energy consumption by up to 40% compared to conventional heating systems, while maintaining a comfortable indoor temperature. The fuzzy control system provides precise control of the heating power and ensures efficient use of the renewable energy source. The main conclusion of the article is that the proposed smart home heating system is a viable solution for reducing energy consumption and promoting a sustainable lifestyle, especially in areas with abundant renewable energy sources.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135393868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Darko Božanić, Duško Tešić, A. Puška, Anđelka Štilić, Y. R. Muhsen
This paper presents a Fuzzy Inference System (FIS) designed to comprehensively assess challenges, risks, and threats. In the realm of security and defense, defining these elements is inherently uncertain and complex. The paper addresses this challenge by integrating fuzzy logic into the model. As a pivotal instrument for decision-making, the model not only facilitates the precise identification of challenges, risks, and threats but also provides vital support for the strategic and doctrinal document development process. The methodology proves instrumental in reconciling divergent perspectives, aligning theoretical intricacies with practical applications. By effectively capturing the nuanced interplay between variables, the model offers a dynamic framework that enhances the accuracy and efficiency of security-related decision-making.
{"title":"Ranking challenges, risks and threats using Fuzzy Inference System","authors":"Darko Božanić, Duško Tešić, A. Puška, Anđelka Štilić, Y. R. Muhsen","doi":"10.31181/dmame622023926","DOIUrl":"https://doi.org/10.31181/dmame622023926","url":null,"abstract":"This paper presents a Fuzzy Inference System (FIS) designed to comprehensively assess challenges, risks, and threats. In the realm of security and defense, defining these elements is inherently uncertain and complex. The paper addresses this challenge by integrating fuzzy logic into the model. As a pivotal instrument for decision-making, the model not only facilitates the precise identification of challenges, risks, and threats but also provides vital support for the strategic and doctrinal document development process. The methodology proves instrumental in reconciling divergent perspectives, aligning theoretical intricacies with practical applications. By effectively capturing the nuanced interplay between variables, the model offers a dynamic framework that enhances the accuracy and efficiency of security-related decision-making.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42822900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hasan Daneshvar, S. Niroomand, Omid Boyer, A. Hadi-Vencheh
Given that finding the right and appropriate route in the daytime and busy city with the occurred traffic limitations is a major problem that not only causes inefficient performance in distribution networks but also causes irreparable environmental damage to society. This study focuses on improving the routing of the goods distribution network using the intelligent transportation system. In this regard, first, the problem is modeled, and then an intelligent transportation system is combined with some meta-heuristic algorithms to solve it. In the proposed algorithm, we first use the clustering algorithm to cluster location of customers and then create sub-clusters based on the time window. The proposed routes are created by using the genetic and particle swarm optimization meta-heuristic algorithms as the static part of the approach, and if the traffic conditions change, the Vehicular Ad - hoc Network (Vanet), which is one of the sub-systems of the intelligent transportation system as the dynamic part of the approach checks the new traffic conditions and sends the new information to the proposed algorithms to recheck the route. The Aarhus-Denmark data set is selected due to having urban traffic information, meteorology, and urban areas. This is related to the City Pulse project. According to the obtained results, in terms of reducing the cost of transmission, including the cost of service delay and total cost of moving, the proposed method reached better solutions comparing to the meta-heuristic algorithms of literature.
{"title":"Designing a hybrid intelligent transportation system for optimization of goods distribution network routing problem","authors":"Hasan Daneshvar, S. Niroomand, Omid Boyer, A. Hadi-Vencheh","doi":"10.31181/dma622023899","DOIUrl":"https://doi.org/10.31181/dma622023899","url":null,"abstract":"Given that finding the right and appropriate route in the daytime and busy city with the occurred traffic limitations is a major problem that not only causes inefficient performance in distribution networks but also causes irreparable environmental damage to society. This study focuses on improving the routing of the goods distribution network using the intelligent transportation system. In this regard, first, the problem is modeled, and then an intelligent transportation system is combined with some meta-heuristic algorithms to solve it. In the proposed algorithm, we first use the clustering algorithm to cluster location of customers and then create sub-clusters based on the time window. The proposed routes are created by using the genetic and particle swarm optimization meta-heuristic algorithms as the static part of the approach, and if the traffic conditions change, the Vehicular Ad - hoc Network (Vanet), which is one of the sub-systems of the intelligent transportation system as the dynamic part of the approach checks the new traffic conditions and sends the new information to the proposed algorithms to recheck the route. The Aarhus-Denmark data set is selected due to having urban traffic information, meteorology, and urban areas. This is related to the City Pulse project. According to the obtained results, in terms of reducing the cost of transmission, including the cost of service delay and total cost of moving, the proposed method reached better solutions comparing to the meta-heuristic algorithms of literature.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43225045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research aims to provide an innovative framework for evaluating airline performance through the networking of decision-making units (DMUs) and neutrosophic data. As a consequence, we propose a comprehensive methodology for assessing the efficiency of these decision-making units. Network data envelopment analysis (DEA) models deal with measurements of relative efficiency of DMUs when the insight of their internal structures is available. In network models, sub-processes are connected by links or intermediate products. Links have the dual role of output from one division or sub-process and input to another one. Therefore, improving the efficiency score of one division by increasing its output may reduce the score of another division because of increasing its input. To address this conflict, we proposed a new approach in Slack-Based Measure (SBM) framework and neutrosophic logic, which provide deeper insights regarding the sources of inefficiency. Our approach is a new network model, in which the intermediate products are classified into two groups of “input-type”, and “output-type” that their excesses and shortfalls directly concern with the objective function. The results of the illustrated case and analysis show that the constructed model may successfully produce performance assessments. By taking into account the number of slacks or surpluses of these products in the objective function, the proposed model gives analysts and managers a more accurate assessment of network structure efficiency. In this paper, we present a new model in the field of network data envelopment analysis with SBM approach in a neutrosphonic environment, in which for the first time the nature of intermediate products in terms of input or output is investigated. Also, the proposed framework is the first attempt to performance evaluation in neutrosophic network DEA.
{"title":"A comprehensive neutrosophic model for evaluating the efficiency of airlines based on SBM model of network DEA","authors":"Reza Rasinojehdehi, H. B. Valami","doi":"10.31181/dma622023729","DOIUrl":"https://doi.org/10.31181/dma622023729","url":null,"abstract":"This research aims to provide an innovative framework for evaluating airline performance through the networking of decision-making units (DMUs) and neutrosophic data. As a consequence, we propose a comprehensive methodology for assessing the efficiency of these decision-making units. Network data envelopment analysis (DEA) models deal with measurements of relative efficiency of DMUs when the insight of their internal structures is available. In network models, sub-processes are connected by links or intermediate products. Links have the dual role of output from one division or sub-process and input to another one. Therefore, improving the efficiency score of one division by increasing its output may reduce the score of another division because of increasing its input. To address this conflict, we proposed a new approach in Slack-Based Measure (SBM) framework and neutrosophic logic, which provide deeper insights regarding the sources of inefficiency. Our approach is a new network model, in which the intermediate products are classified into two groups of “input-type”, and “output-type” that their excesses and shortfalls directly concern with the objective function. The results of the illustrated case and analysis show that the constructed model may successfully produce performance assessments. By taking into account the number of slacks or surpluses of these products in the objective function, the proposed model gives analysts and managers a more accurate assessment of network structure efficiency. In this paper, we present a new model in the field of network data envelopment analysis with SBM approach in a neutrosphonic environment, in which for the first time the nature of intermediate products in terms of input or output is investigated. Also, the proposed framework is the first attempt to performance evaluation in neutrosophic network DEA.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42398249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nourhan El. Gharieb Mohammad, Yassmen Youssef Rawash, S. Aly, M. Awad, Mostafa Hassanein Hussein Mohamed
The optimization of gas pipeline networks is critical for efficient and cost-effective transportation of natural gas. This study develops a mathematical model capable of analyzing different network configurations, including branched and branched-cyclic topologies, to explore the optimization of gas pipeline network conditions. The research provides valuable insights into the gas pipeline network optimization process, empowering industry stakeholders to make informed decisions and enhance performance in terms of efficiency, reliability, and cost-effectiveness. To attain these objectives, this study utilizes advanced simulation tools, state-of-the-art optimization algorithms, and sophisticated mathematical models that accurately represent the network's behavior. The optimization process aims to minimize the network's power requirements while simultaneously maximizing gas flow rate and optimizing line pack, ensuring optimal utilization of the pipeline infrastructure. The VIKOR (VIekriterijumsko KOmpromisno Rangiranje) method is identifying the most optimal network configuration and operating conditions. Our analysis applies this approach to three case studies, demonstrating its effectiveness in identifying the best network configurations. Additionally, the calculations of total cost and fuel consumption coincide with relative closeness, which confirms the accuracy of our proposed method, whereas optimal scenarios of the three cases have the minimum total cost among all scenarios. In conclusion, this research successfully develops a mathematical model and optimization approach to tackle the complexities of gas pipeline network optimization. The application of The VIKOR method and the analysis of case studies offer substantial evidence of its effectiveness.
{"title":"Enhancing gas pipeline network efficiency through VIKOR method","authors":"Nourhan El. Gharieb Mohammad, Yassmen Youssef Rawash, S. Aly, M. Awad, Mostafa Hassanein Hussein Mohamed","doi":"10.31181/dmame622023868","DOIUrl":"https://doi.org/10.31181/dmame622023868","url":null,"abstract":"The optimization of gas pipeline networks is critical for efficient and cost-effective transportation of natural gas. This study develops a mathematical model capable of analyzing different network configurations, including branched and branched-cyclic topologies, to explore the optimization of gas pipeline network conditions. The research provides valuable insights into the gas pipeline network optimization process, empowering industry stakeholders to make informed decisions and enhance performance in terms of efficiency, reliability, and cost-effectiveness. To attain these objectives, this study utilizes advanced simulation tools, state-of-the-art optimization algorithms, and sophisticated mathematical models that accurately represent the network's behavior. The optimization process aims to minimize the network's power requirements while simultaneously maximizing gas flow rate and optimizing line pack, ensuring optimal utilization of the pipeline infrastructure. The VIKOR (VIekriterijumsko KOmpromisno Rangiranje) method is identifying the most optimal network configuration and operating conditions. Our analysis applies this approach to three case studies, demonstrating its effectiveness in identifying the best network configurations. Additionally, the calculations of total cost and fuel consumption coincide with relative closeness, which confirms the accuracy of our proposed method, whereas optimal scenarios of the three cases have the minimum total cost among all scenarios. In conclusion, this research successfully develops a mathematical model and optimization approach to tackle the complexities of gas pipeline network optimization. The application of The VIKOR method and the analysis of case studies offer substantial evidence of its effectiveness.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44405541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Amiri, M. Rostamy-Malkhalifeh, F. Lotfi, M. Mozaffari
: The importance of insurance companies in the economic growth of countries has led to them, so in this article, the efficiency of insurance companies is measured based on inputs, favorable and unfavorable outputs. The developed model, unlike the previous models, considers the unfavorable outputs of insurance companies in conditions of uncertainty with fuzzy data based on different views of experts. The required data for each of the inputs and outputs have been provided by experts in the form of triangular fuzzy numbers. The existence of different views of experts, including optimistic, likely, and pessimistic, has led to its impact on the returns to the scale of insurance companies. The results of the survey of 24 insurance companies in Iran, based on the different views of experts, show that the more optimistic the experts' view is, the higher the average return on the scale of insurance companies compared to other views. As the expert view has shifted from optimistic to pessimistic, returns to full scale for insurance companies have declined. In this way, the average return to the scale of all insurance companies is equal to 0.8972 in the optimistic view, in the probable view it is equal to 0.8863 and in the pessimistic view it is equal to 0.8336. The uncertainty rate also affects the inputs, desirable and undesirable outputs of the model, and with the increase of this rate, the desirable inputs and outputs decrease and the undesirable outputs increase. The result of this is the reduction of the average return to the scale of insurance companies with the increase of the uncertainty rate.
{"title":"Measuring returns to scale based on the triangular fuzzy DEA approach with different views of experts: Case study of Iranian insurance companies","authors":"M. Amiri, M. Rostamy-Malkhalifeh, F. Lotfi, M. Mozaffari","doi":"10.31181/dmame622023740","DOIUrl":"https://doi.org/10.31181/dmame622023740","url":null,"abstract":": The importance of insurance companies in the economic growth of countries has led to them, so in this article, the efficiency of insurance companies is measured based on inputs, favorable and unfavorable outputs. The developed model, unlike the previous models, considers the unfavorable outputs of insurance companies in conditions of uncertainty with fuzzy data based on different views of experts. The required data for each of the inputs and outputs have been provided by experts in the form of triangular fuzzy numbers. The existence of different views of experts, including optimistic, likely, and pessimistic, has led to its impact on the returns to the scale of insurance companies. The results of the survey of 24 insurance companies in Iran, based on the different views of experts, show that the more optimistic the experts' view is, the higher the average return on the scale of insurance companies compared to other views. As the expert view has shifted from optimistic to pessimistic, returns to full scale for insurance companies have declined. In this way, the average return to the scale of all insurance companies is equal to 0.8972 in the optimistic view, in the probable view it is equal to 0.8863 and in the pessimistic view it is equal to 0.8336. The uncertainty rate also affects the inputs, desirable and undesirable outputs of the model, and with the increase of this rate, the desirable inputs and outputs decrease and the undesirable outputs increase. The result of this is the reduction of the average return to the scale of insurance companies with the increase of the uncertainty rate.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48005779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehdi VakilZadeh, M. Shayanfar, M. Zabihi‑Samani, M. Ravanshadnia
As a part of human resource management, active companies in Iran's railway industry must determine the qualifications for appropriate project managers in railway construction. This research aims to consider the importance of Iran's railway construction projects due to the lack of staff with expertise and their high economic impact and budget. A decision-making model is presented. The project manager's qualifications are determined through questionnaires answered by experts in the field. The numerical model is created to determine the qualifications for project management in the railway industry. Therefore, Competency-Based Selection by Genetic Programming Multigenic Regression (CSPR) is proposed for project-oriented human resource management. Decision-making is done in three phases: Hierarchical analysis process for evaluating and determining the qualifications based on the questionnaires. The model is trained and validated by creating optimal coefficients and genes to determine the contribution of each of these qualifications in determining each candidate's final qualifications based on experts' questionnaires. Finally, the model's accuracy with optimal coefficients will be tested based on the questionnaires not used in the model training phase. The CSPR model provides a qualitative method and numerical optimization to evaluate and grade the project manager in Iran's railway construction projects based on the metaheuristic method.
{"title":"Competency-based selection and assignment for project manager in Iranian railways projects by genetic multigenic programming","authors":"Mehdi VakilZadeh, M. Shayanfar, M. Zabihi‑Samani, M. Ravanshadnia","doi":"10.31181/dmame622023727","DOIUrl":"https://doi.org/10.31181/dmame622023727","url":null,"abstract":"As a part of human resource management, active companies in Iran's railway industry must determine the qualifications for appropriate project managers in railway construction. This research aims to consider the importance of Iran's railway construction projects due to the lack of staff with expertise and their high economic impact and budget. A decision-making model is presented. The project manager's qualifications are determined through questionnaires answered by experts in the field. The numerical model is created to determine the qualifications for project management in the railway industry. Therefore, Competency-Based Selection by Genetic Programming Multigenic Regression (CSPR) is proposed for project-oriented human resource management. Decision-making is done in three phases: Hierarchical analysis process for evaluating and determining the qualifications based on the questionnaires. The model is trained and validated by creating optimal coefficients and genes to determine the contribution of each of these qualifications in determining each candidate's final qualifications based on experts' questionnaires. Finally, the model's accuracy with optimal coefficients will be tested based on the questionnaires not used in the model training phase. The CSPR model provides a qualitative method and numerical optimization to evaluate and grade the project manager in Iran's railway construction projects based on the metaheuristic method.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43388749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kongkoon Tochaiwat, Patcharida Pultawee, D. Rinchumphu
Although the predicted number of sold units per month is one of the most necessary information to study the feasibility of detached-housing estate projects, traditional forecasting methods are limited. The research objective was to apply the Artificial Neural Network (ANN) technique to develop a sales rate forecasting model by compiling factors from an appropriate literature review. Then, 100 housing project data were collected from market research reports and the projects' websites and analyzed using the ANN technique. The results showed the ANN network with 16 input nodes from 10 factors: Selling price, Number of bathrooms, Number of bedrooms, Distance from the main road, Distance from the bus stop, Distance from the expressway, Distance from the metro station, Distance from the gas station, Distance from the shopping mall, and Project location zone. The acquired model had a Root Mean Square Error (RMSE) of ±6.296, and the slope and R2 values of the linear regression analysis between the forecasted rate and the actual rate were 0.620 and 0.571, respectively. The findings guide real estate developers and academia on the factors affecting the sales rate and provide a decision support model for investment and design of projects and confirm the potential of ANN in solving the problem with limited numbers of data.
{"title":"Sales rate forecasting of single-detached houses using artificial neural network technique","authors":"Kongkoon Tochaiwat, Patcharida Pultawee, D. Rinchumphu","doi":"10.31181/dmame622023707","DOIUrl":"https://doi.org/10.31181/dmame622023707","url":null,"abstract":"Although the predicted number of sold units per month is one of the most necessary information to study the feasibility of detached-housing estate projects, traditional forecasting methods are limited. The research objective was to apply the Artificial Neural Network (ANN) technique to develop a sales rate forecasting model by compiling factors from an appropriate literature review. Then, 100 housing project data were collected from market research reports and the projects' websites and analyzed using the ANN technique. The results showed the ANN network with 16 input nodes from 10 factors: Selling price, Number of bathrooms, Number of bedrooms, Distance from the main road, Distance from the bus stop, Distance from the expressway, Distance from the metro station, Distance from the gas station, Distance from the shopping mall, and Project location zone. The acquired model had a Root Mean Square Error (RMSE) of ±6.296, and the slope and R2 values of the linear regression analysis between the forecasted rate and the actual rate were 0.620 and 0.571, respectively. The findings guide real estate developers and academia on the factors affecting the sales rate and provide a decision support model for investment and design of projects and confirm the potential of ANN in solving the problem with limited numbers of data.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49300851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Chaudhuri, Soham Mitra, Banhi Guha, S. Biswas, Pankaj Kumar
Over the years corporate social responsibility (CSR) has become a source of competitive advantage for firms including banks. CSR is one of the important aspects of a private bank’s contribution to society apart from its functionality. The extant literature shows a scantiness of research concerning the assessment of the efficiency of banks in CSR expenditure towards environmental sustainability. The current work fills the gap in the literature by providing a multi-objective assessment framework to measure and compare the leading private banks based on their efficiency in CSR vis-à-vis environmental sustainability. This paper aims to study the ideal and actual contribution of the Indian private banking sector toward environmental sustainability and other sectors. This is done by using data from 10 private sector banks over 7 financial years and comparing their efficiencies over time using optimization techniques like Data Envelopment Analysis. To study the change in CSR contribution over time, the Malmquist Index has been used. City Union and HDFC have shown the highest contribution towards environmental sustainability as a part of their CSR acts consistently over the years irrespective of the income generated. The outcome of the present paper shall enable the decision-makers to formulate of the appropriate policies.
{"title":"CSR Contributions for Environmental Sustainability: A comparison of private banks in emerging market","authors":"T. Chaudhuri, Soham Mitra, Banhi Guha, S. Biswas, Pankaj Kumar","doi":"10.31181/dmame622023852","DOIUrl":"https://doi.org/10.31181/dmame622023852","url":null,"abstract":"Over the years corporate social responsibility (CSR) has become a source of competitive advantage for firms including banks. CSR is one of the important aspects of a private bank’s contribution to society apart from its functionality. The extant literature shows a scantiness of research concerning the assessment of the efficiency of banks in CSR expenditure towards environmental sustainability. The current work fills the gap in the literature by providing a multi-objective assessment framework to measure and compare the leading private banks based on their efficiency in CSR vis-à-vis environmental sustainability. This paper aims to study the ideal and actual contribution of the Indian private banking sector toward environmental sustainability and other sectors. This is done by using data from 10 private sector banks over 7 financial years and comparing their efficiencies over time using optimization techniques like Data Envelopment Analysis. To study the change in CSR contribution over time, the Malmquist Index has been used. City Union and HDFC have shown the highest contribution towards environmental sustainability as a part of their CSR acts consistently over the years irrespective of the income generated. The outcome of the present paper shall enable the decision-makers to formulate of the appropriate policies.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44834114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-15DOI: 10.31181/dmame060129022023j
Madan Jagtap, P. Karande
Using improvements to the recently published m-polar fuzzy set (mFS) elimination and choice translating reality-I (ELECTRE-I) approach for calculating criteria weights, the selection of a Non-Traditional Machining (NTM) process problem from the industry is solved in this research. The criteria weights for the m-polar fuzzy ELECTRE-I method are evaluated using the Analytical Hierarchy Process (AHP) approach and the Revised Simos' method. For the ELECTRE family's criteria weight calculations, the Simos’ approach has been revised. Many researchers calculated the weight of the criteria in the selection of the NTM process using the AHP approach. Problems with both physical and intangible properties can be solved using the m-polar fuzzy ELECTRE-I approach. Additionally, it has the ability to solve MCDM issues with more variables. The improved Simos' technique is used in this work because it incorporates user choices for the criteria, or user voting for the criterion. Using expert assistance, the AHP technique prioritizes the criterion based on pair-by-pair comparisons of the criteria. The AHP approach makes compromises between the criteria. The ultimate selection of the process based on the needed aim is affected by both tangible and intangible features in the NTM selection dilemma. The impact of criteria weight techniques on the choice of the NTM process is examined using a single dimensional sensitivity analysis. AHP approach is proven to be less stable for criteria weight variation than the improved Simos' weight calculation method. The updated Simos' method, which takes into account user preferences, performs better for the m-polar fuzzy ELECTRE-I algorithm than the AHP weight calculation method.
利用对最近发表的m极模糊集(mFS)消除和选择转换现实- i (electrei)方法的改进来计算标准权重，解决了工业中非传统加工(NTM)工艺的选择问题。采用层次分析法(AHP)和修正Simos法对m极模糊elecre - i方法的准则权重进行了评价。对于ELECTRE系列的标准重量计算，Simos的方法已经进行了修改。许多研究者使用AHP方法计算了NTM过程中选择标准的权重。具有物理和无形属性的问题可以使用m极模糊elect - i方法来解决。此外，它还具有使用更多变量解决MCDM问题的能力。在这项工作中使用了改进的Simos技术，因为它结合了用户对标准的选择，或者用户对标准的投票。利用专家协助，AHP技术基于对标准的成对比较来确定标准的优先级。AHP方法在两个标准之间做出妥协。在NTM选择困境中，基于所需目标的过程最终选择受到有形和无形特征的双重影响。标准权重技术对NTM工艺选择的影响是使用单维灵敏度分析进行检验的。AHP方法对于准则权重变化的稳定性不如改进的Simos权重计算方法。改进后的Simos方法考虑了用户偏好，对m极模糊electrei算法的性能优于AHP权重计算方法。
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